Data-independent Acquisition Method Research Articles

Mass defect-based carbonyl activated tags (mdCATs) for multiplex data-independent acquisition proteome quantification.

Mass spectrometry (MS) quantification has become an essential tool for both modern biology and translational medicine research. Data-independent acquisition (DIA) has emerged recently and combines the merits of data-dependent acquisition (DDA) methods and selected reaction monitoring (SRM) approaches. Unfortunately, making a quantitative comparison between samples in a single DIA injection is extremely restricted due to its poor compatibility with the traditional DDA labeling approach. As a consequence, a multiplex quantitative reagent suitable for the DIA strategy would be strongly desirable to improve these uninformative situations. As counterparts to traditional DDA quantitative reagents, such as tandem mass tags (TMT) and isobaric tags for relative and absolute quantification (iTRAQ), here, we have designed a novel mass-defect-based carbonyl activated tag (mdCAT) allowing the DIA method to quantify eight samples in parallel for the first time. The integration of the mdCATs with the DIA strategy can not only allow the popular and powerful merits of the DIA strategy, such as broad proteomic coverage, good reproducibility, and accuracy, but it can also eliminate spectral complexity due to their minuscule mass differences. In doing so, it offers new opportunities for the investigation of clinical samples, driving the field of DIA toward unprecedented multiplexing and improving its ability to search for diagnostic biomarkers.

Establishing a Custom-Fit Data-Independent Acquisition Method for Label-Free Proteomics.

Data-independent acquisition (DIA) hasrecently developed as a powerful tool to enhance the quantification of peptides and proteins within a variety of sample types, by overcoming the stochastic nature of classical data-dependent approaches, as well as by enabling the identification of all peptides detected in a mass spectrometric event. Here, we describe a workflow for the establishment of a sample-fitting DIA method using Spectronaut Pulsar X (Biognosys, Switzerland).

Profiling of Low-Molecular-Weight Carbonyls and Protein Modifications in Flavored Milk.

Thermal treatments of dairy products favor oxidations, Maillard reactions, and the formation of sugar or lipid oxidation products. Additives including flavorings might enhance these reactions or even induce further reactions. Here we aimed to characterize protein modifications in four flavored milk drinks using samples along the production chain—raw milk, pasteurization, mixing with flavorings, heat treatment, and the commercial product. Therefore, milk samples were analyzed using a bottom up proteomics approach and a combination of data-independent (MSE) and data-dependent acquisition methods (DDA). Twenty-one small carbonylated lipids were identified by shotgun lipidomics triggering 13 protein modifications. Additionally, two Amadori products, 12 advanced glycation end products (AGEs), and 12 oxidation-related modifications were targeted at the protein level. The most common modifications were lactosylation, formylation, and carboxymethylation. The numbers and distribution of modification sites present in raw milk remained stable after pasteurization and mixing with flavorings, while the final heat treatment significantly increased lactosylation and hexosylation in qualitative and quantitative terms. The processing steps did not significantly affect the numbers of AGE-modified, oxidized/carbonylated, and lipid-carbonylated sites in proteins.

Comparative Proteomic Profiling of Marine and Freshwater Synechocystis Strains Using Liquid Chromatography-Tandem Mass Spectrometry

Freshwater Synechocystis sp. PCC 6803 has been considered to be a platform for the production of the next generation of biofuels and is used as a model organism in various fields. Various genomics, transcriptomics, metabolomics, and proteomics studies have been performed on this strain, whereas marine Synechocystis sp. PCC 7338 has not been widely studied despite its wide distribution. This study analyzed the proteome profiles of two Synechocystis strains using a liquid chromatography–tandem mass spectrometry-based bottom-up proteomic approach. Proteomic profiling of Synechocystis sp. PCC 7338 was performed for the first time with a data-dependent acquisition method, revealing 18,779 unique peptides and 1794 protein groups. A data-independent acquisition method was carried out for the comparative quantitation of Synechocystis sp. PCC 6803 and 7338. Among 2049 quantified proteins, 185 up- and 211 down-regulated proteins were defined in Synechocystis sp. PCC 7338. Some characteristics in the proteome of Synechocystis sp. PCC 7338 were revealed, such as its adaptation to living conditions, including the down-regulation of some photosynthesis proteins, the up-regulation of kdpB, and the use of osmolyte glycine as a substrate in C1 metabolism for the regulation of carbon flow. This study will facilitate further studies on Synechocystis 7338 to define in depth the proteomic differences between it and other Synechocystis strains.

Optimized Sample Preparation and Data Processing of Data-Independent Acquisition Methods for the Robust Quantification of Trace-Level Host Cell Protein Impurities in Antibody Drug Products.

Host cell proteins (HCPs) are a major class of bioprocess-related impurities generated by the host organism and are generally present at low levels in purified biopharmaceutical products. The monitoring of these impurities is identified as an important critical quality attribute of monoclonal antibody (mAb) formulations not only due to the potential risk for the product stability and efficacy but also concerns linked to the immunogenicity of some of them. While overall HCP levels are usually monitored by enzyme-linked immunosorbent assay (ELISA), mass spectrometry (MS)-based approaches have been emerging as powerful and promising alternatives providing qualitative and quantitative information. However, a major challenge for liquid chromatography (LC)-MS-based methods is to deal with the wide dynamic range of drug products and the extreme sensitivity required to detect trace-level HCPs. In this study, we developed powerful and reproducible MS-based analytical workflows coupling optimized and efficient sample preparations, the library-free data-independent acquisition (DIA) method, and stringent validation criteria. The performances of several preparation protocols and DIA versus classical data-dependent acquisition (DDA) were evaluated using a series of four commercially available drug products. Depending on the selected protocols, the user has access to different information: on the one hand, a deep profiling of tens of identified HCPs and on the other hand, accurate and reproducible (coefficients of variation (CVs) < 12%) quantification of major HCPs. Overall, a final global HCP amount of a few tens of ng/mg mAb in these mAb samples was measured, while reaching a sensitivity down to the sub-ng/mg mAb level. Thus, this straightforward and robust approach can be intended as a routine quality control for any drug product analysis.

PulseDIA: Data-Independent Acquisition Mass Spectrometry Using Multi-Injection Pulsed Gas-Phase Fractionation.

The performance of data-independent acquisition (DIA) mass spectrometry (MS) depends on the separation efficiency of peptide precursors. In Orbitrap-based mass spectrometers, separation efficiency of peptide precursors is limited by the relatively slow scanning rate compared to time of flight (TOF)-based MS. Here, we present PulseDIA, a multi-injection gas-phase fractionation (GPF) strategy for enhanced DIA-MS. This is achieved by equally dividing the conventional DIA analysis covering the entire mass range into multiple injections for DIA analyses with complementary windows. Using mouse liver digests, the PulseDIA method identified up to 50% more peptides and 29% more protein groups than that by conventional DIA with the same length of effective gradient time. Compared to conventional multi-injection GPF, PusleDIA exhibited higher flexibility and identified up to 18% more peptides and 8% more protein groups using two injections. The gain of peptides per effective time unit was the highest in PulseDIA compared to conventional DIA and GPF. We further applied the PulseDIA method to profile the proteome of 18 human tissue samples (benign and malignant) from nine cholangiocarcinoma (CCA) patients. PulseDIA identified 7796 protein groups in these CCA samples, with a 14% increase of protein group identification compared to the conventional DIA method. The missing value for protein matrix dropped by 7% using PulseDIA compared to DIA. A total of 681 significantly altered proteins were detected in CCA samples using PulseDIA, including several dysregulated proteins, which were absent in the conventional DIA analysis. Taken together, we present PulseDIA as an enhanced DIA-MS method with improved sensitivity and reproducibility.

Probing SWATH-MS as a tool for proteome level quantification in a nonmodel fish.

Quantitative proteomics via mass spectrometry can provide valuable insight into molecular and phenotypic characteristics of a living system. Recent mass spectrometry developments include data‐independent acquisition (SWATH/DIA‐MS), an accurate, sensitive and reproducible method for analysing the whole proteome. The main requirement for this method is the creation of a comprehensive spectral library. New technologies have emerged producing larger and more accurate species‐specific libraries leading to a progressive collection of proteome references for multiple molecular model species. Here, for the first time, we set out to compare different spectral library constructions using multiple tissues from a coral reef fish to demonstrate its value and feasibility for nonmodel organisms. We created a large spectral library composed of 12,553 protein groups from liver and brain tissues. Via identification of differentially expressed proteins under fish exposure to elevated pCO2 and temperature, we validated the application and usefulness of these different spectral libraries. Successful identification of significant differentially expressed proteins from different environmental exposures occurred using the library with a combination of data‐independent and data‐dependent acquisition methods as well as both tissue types. Further analysis revealed expected patterns of significantly up‐regulated heat shock proteins in a dual condition of ocean warming and acidification indicating the biological accuracy and relevance of the method. This study provides the first reference spectral library for a nonmodel organism. It represents a useful guide for future building of accurate spectral library references in nonmodel organisms allowing the discovery of ecologically relevant changes in the proteome.

Neuropeptidomic Profiling and Localization in the Crustacean Cardiac Ganglion Using Mass Spectrometry Imaging with Multiple Platforms.

The crustacean cardiac neuromuscular system is a useful model for studying how neural circuits generate behavior, as it is comprised of a simple ganglion containing nine neurons, yet acts as a robust central pattern generator. The crustacean heart is neurogenic, receiving input from neuropeptides. However, the specific effects of neuropeptides on cardiac output is not fully understood, and the large degree of comodulation between multiple neuropeptides makes studying these effects more challenging. To address this challenge, matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) imaging was used to localize neuropeptides within the cardiac ganglion (CG), providing information about the identity and localization of neuropeptides being present. CG extracts were also profiled using liquid chromatography coupled to tandem mass spectrometry (MS/MS) with a data independent acquisition method, resulting in the confirmation of 316 neuropeptides. Two MS imaging (MSI) platforms were compared to provide comprehensive results, including a MALDI-Orbitrap instrument for high mass spectral resolution for accurate identifications and a MALDI TOF/TOF instrument for improved spatial resolution and sensitivity, providing more descriptive MS images. MS images for 235 putative neuropeptides were obtained, with the identification of 145 of these being confirmed by either complementary MS/MS data or accurate mass matching. The MSI studies demonstrate the sensitivity and power of this MALDI-based in situ analytical strategy for unraveling the chemical complexity present in a small nine-cell neuronal system. The results of this study will enable more informative assays of the functions of neuropeptides within this important neural circuit.

Data-Independent Acquisition Proteomics Unravels the Effects of Iron Ions on Coronatine Synthesis in Pseudomonas syringae pv. tomato DC3000.

Coronatine (COR) is a new type of plant growth regulator that is produced by Pseudomonas syringae pathovars and plays an important role in modulating plant growth, development, and tolerance to multiple stresses. However, the factors affecting COR production are not very clear. In this study, the effects of FeCl3 on COR production were researched. The data-independent acquisition (DIA) approach, which is a proteomic quantitative analysis method, was applied to quantitatively trace COR production and proteomic changes in P. syringae pv. tomato DC3000 under different FeCl3 culture conditions. The results showed that COR production increased with the addition of FeCl3 and that there was significant upregulation in the expression of proteins related to COR synthesis and regulation. In addition, FeCl3 also affected the expression of related proteins involved in various metabolic pathways such as glycolysis and the tricarboxylic acid cycle. Moreover, various precursors such as isoleucine and succinate semialdehyde, as well as other related proteins involved in the COR synthesis pathway, were significantly differentially expressed. Our findings revealed the dynamic regulation of COR production in response to FeCl3 at the protein level and showed the potential of using the DIA method to track the dynamic changes of the P. syringae pv. tomato DC3000 proteome during COR production, providing an important reference for future research on the regulatory mechanism of COR biosynthesis and theoretical support for COR fermentation production.

Combinatory Data-Independent Acquisition and Parallel Reaction Monitoring Method for Deep Profiling of Gangliosides.

Ganglioside is an important class of lipid species involved in intercellular signaling and various diseases, especially for neurodegenerative diseases. Systematic ganglioside profiling is challenging because of their naturally low abundance and highly diverse species. Herein, a new data-independent acquisition and parallel reaction monitoring (DIA/PRM) method with superior sensitivity was developed. The untargeted DIA acquisition consecutively records all the precursor ion and fragment ions at the same time, while the targeted PRM analysis with versatile higher collisional dissociation generates full MS/MS spectra for structure elucidation and verification. As compared with traditional data-dependent acquisition (DDA), the DIA/PRM method unbiasedly detected the majority of abundant ganglioside species and as low as 50 pg of ganglioside in an untargeted manner. Gangliosides in four kinds of biological samples including the mouse brain, mouse plasma, HeLa cell, and human colon cancer tissue were systematically identified, and low-abundance ganglioside species were further extended on the basis of linear chromatography retention rules of the most frequently detected ganglioside species. A total of 383 ganglioside features were defined with 329 of them derived from 32 ganglioside species. Taking advantage of the high-resolution MS analysis, rare ganglioside species were further elucidated according to their characteristic fragment ions and neutral losses. In total, 18 gangliosides with a ceramide carbon number from 20 to 25 and modified gangliosides, including 18 acetylated, 8 diacetylated, 1 phosphorylated, 36 N-glycolyneuraminic acid (NeuGc)-containing, and 7 di-NeuGc-containing gangliosides, were newly identified. The developed DIA/PRM method therefore generated a rich ganglioside resource for further functional exploration and is a unique alternative for DDA analysis for global ganglioside profiling in various biological systems.

Mass Defect-Based DiLeu Tagging for Multiplexed Data-Independent Acquisition.

The unbiased selection of peptide precursors makes data-independent acquisition (DIA) an advantageous alternative to data-dependent acquisition (DDA) for discovery proteomics, but traditional multiplexed quantification approaches employing mass difference labeling or isobaric tagging are incompatible with DIA. Here, we describe a strategy that permits multiplexed quantification by DIA using mass defect-based N,N-dimethyl leucine (mdDiLeu) tags and high-resolution tandem mass spectrometry (MS2) analysis. Millidalton mass differences between mdDiLeu isotopologues produce fragment ion multiplet peaks separated in mass by as little as 5.8 mDa, enabling up to 4-plex quantification in DIA MS2 spectra. Quantitative analysis of yeast samples displayed comparable accuracy and precision for MS2-based DIA and MS1-based DDA methods. Multiplexed DIA analysis of cerebrospinal fluid revealed the dynamic proteome changes in Alzheimer's disease, demonstrating its utility for discovery of potential clinical biomarkers. We show that the mdDiLeu tagging approach for multiplexed DIA is a viable methodology for investigating proteome changes, particularly for low-abundance proteins, in different biological matrices.

Acquiring and Analyzing Data Independent Acquisition Proteomics Experiments without Spectrum Libraries

Data independent acquisition (DIA) is an attractive alternative to standard shotgun proteomics methods for quantitative experiments. However, most DIA methods require collecting exhaustive, sample-specific spectrum libraries with data dependent acquisition (DDA) to detect and quantify peptides. In addition to working with non-human samples, studies of splice junctions, sequence variants, or simply working with small sample yields can make developing DDA-based spectrum libraries impractical. Here we illustrate how to acquire, queue, and validate DIA data without spectrum libraries, and provide a workflow to efficiently generate DIA-only chromatogram libraries using gas-phase fractionation (GPF). We present best-practice methods for collecting DIA data using Orbitrap-based instruments and develop an understanding for why DIA using an Orbitrap mass spectrometer should be approached differently than when using time-of-flight instruments. Finally, we discuss several methods for analyzing DIA data without libraries.

An integrated data-dependent and data-independent acquisition method for hazardous compounds screening in foods using a single UHPLC-Q-Orbitrap run

Thousands of hazardous compounds that contaminate foods and feeds pose potential risks for human and animal health. However, it remains a challenge to perform a fast monitoring for safety surveillance. Herein we report a novel approach, integrated data-dependent and data-independent acquisition (DDIA) method, to efficiently screen for hundreds of chemicals in a single run using ultra-high-performance liquid chromatography coupled with quadrupole Orbitrap high-resolution mass spectrometry (UHPLC-Q-Orbitrap). This method was successfully applied to analyze 180 veterinary drugs in milk, 220 pesticides in tomato and 50 mycotoxins in maize, respectively. Compared with the widely used approaches of data-dependent acquisition (DDA) or data-independent acquisition (DIA), the obtained results indicate that DDIA-based method combines the advantages of both DDA and DIA, since it achieves higher reproducibility of identification, lower false results for targeted compounds. Notably, the advantage of DDIA approach is that it enables better date retroactivity for untargeted compounds, such as metabolites and decomposition products. With the improvement in high-resolution mass spectrometry (HRMS) as well as data-mining techniques, we believe that DDIA data acquisition approach based on LC-HRMS will be widely applied in various fields in the near future, especially in compound screening and omics field, such as metabolomics and proteomics.

SWATH-MS for metabolomics and lipidomics: critical aspects of qualitative and quantitative analysis.

While liquid chromatography coupled to mass spectrometric detection in the selected reaction monitoring detection mode offers the best quantification sensitivity for omics, the number of target analytes is limited, must be predefined and specific methods developed. Data independent acquisition (DIA), including SWATH using quadrupole time of flight or orbitrap mass spectrometers and generic acquisition methods, has emerged as a powerful alternative technique for quantitative and qualitative analyses since it can cover a wide range of analytes without predefinition. Here we review the current state of DIA, SWATH-MS and highlight novel acquisition strategies for metabolomics and lipidomics and opportunities for data analysis tools. Different databases were searched for papers that report developments and applications of DIA and in particular SWATH-MS in metabolomics and lipidomics. DIA methods generate digital sample records that can be mined retrospectively as further knowledge is gained and, with standardized acquisition schemes, used in multiple studies. The different chemical spaces of metabolites and lipids require different specificities, hence different acquisition and data processing approaches must be considered for their analysis. Although the hardware and acquisition modes are well defined for SWATH-MS, a major challenge for routine use remains the lack of appropriate software tools capable of handling large datasets and large numbers of analytes.

Metabolite identification using an ion mobility enhanced data‐independent acquisition strategy and automated data processing

Liquid chromatography/mass spectrometry is an essential tool for efficient and reliable quantitative and qualitative analysis and underpins much of contemporary drug metabolism and pharmacokinetics. Data-independent acquisition methods such as MSE have reduced the potential to miss metabolites, but do not formally generate quadrupole-resolved product ion spectra. The addition of ion mobility separation to these approaches, for example, in High-Definition MSE (HDMSE ) has the potential to reduce the time needed to set up an experiment and maximize the chance that all metabolites present can be resolved and characterized. We compared High-Definition Data-Dependent Acquisition (HD-DDA), MSE and HDMSE approaches using automated software processing with Mass-MetaSite and WebMetabase. Metabolite identification was performed on incubations of glucagon-like peptide-1 (7-37) (GLP-1) and verapamil hydrochloride. The HD-DDA, MSE and HDMSE experiments were conducted on a Waters ACQUITY UPLC I-Class LC system with a VION IMS quadrupole time-of-flight (QTOF) mass spectrometer operating under UNIFI control. All acquired data were processed using MassMetaSite able to read data from UNIFI 1.9.4. WebMetabase was used to review the detected chromatographic peaks and the spectral data interpretations. A comparison of outcomes obtained for MSE and HDMSE data demonstrated that the same structures were proposed for metabolites of both verapamil and GLP-1. The ratio of structurally matched to mismatched product ions found by MassMetaSite was slightly greater for HDMSE than for MSE , and HD-DDA, thus improving confidence in the structures proposed through the addition of ion mobility based data acquisitions. CONCLUSIONS: HDMSE data acquisition is an effective approach for the elucidation of metabolite structures for both small molecules and peptides, with excellent accuracy and quality, requiring minimal tailoring for the compound under investigation.

Effects of electron-transfer/higher-energy collisional dissociation (EThcD) on phosphopeptide analysis by data-independent acquisition

In quantitative proteomics the use of data-independent acquisition (DIA) methods is getting increasingly popular and is applied to a growing number of sample types ranging from peptidomics to the analysis of post-translational modifications. Several of these sample types have been previously shown to profit from electron-based fragmentation methods such as ETD or EThcD. These fragmentation methods have so far not been implemented in DIA analysis. Here, we show the feasibility of combining DIA with EThcD fragmentation and provide insights into its performance. We show how EThcD can be used to increase peptide coverage, reaching similar success rates during targeted data extraction as standard HCD-based DIA. Furthermore, we illustrate how robust MS1 and LC results can be exploited to circumvent detrimental effects of less efficient fragmentation during targeted data extraction. Ultimately, our data demonstrates how EThcD-based MS/MS spectra can be connected to standard HCD-based DIA analyses, enabling the future use of decision-tree based spectral libraries to query large DIA data sets.

Glycopeptide variable window SWATH for improved data independent acquisition glycoprotein analysis

N-glycosylation plays an essential role in regulating protein folding and function in eukaryotic cells. Sequential window acquisition of all theoretical fragment ion spectra mass spectrometry (SWATH) has proven useful as a data independent acquisition (DIA) MS method for analysis of glycoproteins and their glycan modifications. By separating the entire m/z range into consecutive isolation windows, DIA-MS allows comprehensive MS data acquisition and high-sensitivity detection of molecules of interest. Variable width DIA windows allow optimal analyte measurement, as peptide ions are not evenly distributed across the full m/z range. However, the m/z distribution of glycopeptides is different to that of unmodified peptides because of their large glycan structures. Here, we improved the performance of DIA glycoproteomics by using variable width windows optimized for glycopeptides. This method allocates narrow windows at m/z ranges rich in glycopeptides, improving analytical specificity and performance. We show that related glycoforms must fall in separate windows to allow accurate glycopeptide measurement. We demonstrate the utility of the method by comparing the cell wall glycoproteomes of wild-type and N-glycan biosynthesis deficient yeast and showing improved measurement of glycopeptides with different glycan structures. Our results highlight the importance of appropriately optimized DIA methods for measurement of post-translationally modified peptides.

Partially overlapping sequential window acquisition of all theoretical mass spectra: A methodology to improve the spectra quality of veterinary drugs present at low concentrations in highly complex biological matrices.

Residues of veterinary drugs in food matrices have to be detected, identified and confirmed at low concentrations. Data-independent acquisition (DIA) methods such as the sequential window acquisition of all theoretical spectra (SWATH) permit the extraction of relatively clean spectra out of complex matrices. Such spectra can be significantly improved by using a modified SWATH algorithm which provides several times narrower mass isolation windows without affecting the cycle time. A quadrupole-time-of-flight mass spectrometer was operated in a partially overlapping SWATH mode. Unlike in conventional SWATH, acquisition sequences are not identically repeated, but each sequence is initiated with a mass intercept (mass shift). Pearson correlation is used to assign HRMS-resolved product ions to the precursor mass of interest. Trace analytes (veterinary drugs) in a complex matrix extract (bovine liver) were investigated. Utilizing identical cycle times, the partially overlapping SWATH mode produced for the investigated small molecules a significantly higher selectivity than the conventional SWATH acquisition mode. The acquisition strategy enables long ion accumulation times and therefore the required high sensitivity of detection. The study investigates the quality of the obtained product ion spectra and compares it with that in conventional acquisition modes. The modified SWATH mode permits high duty cycles in combination with narrow virtual mass windows. The technique is a further step toward harvesting a HRMS product ion spectrum out of a data-independent acquisition which moves closer towards the quality of a dedicated precursor unit isolation product ion spectrum.

Deep Proteomics Using Two Dimensional Data Independent Acquisition Mass Spectrometry.

Methodologies that facilitate high-throughput proteomic analysis are a key step toward moving proteome investigations into clinical translation. Data independent acquisition (DIA) has potential as a high-throughput analytical method due to the reduced time needed for sample analysis, as well as its highly quantitative accuracy. However, a limiting feature of DIA methods is the sensitivity of detection of low abundant proteins and depth of coverage, which other mass spectrometry approaches address by two-dimensional fractionation (2D) to reduce sample complexity during data acquisition. In this study, we developed a 2D-DIA method intended for rapid- and deeper-proteome analysis compared to conventional 1D-DIA analysis. First, we characterized 96 individual fractions obtained from the protein standard, NCI-7, using a data-dependent approach (DDA), identifying a total of 151,366 unique peptides from 11,273 protein groups. We observed that the majority of the proteins can be identified from just a few selected fractions. By performing an optimization analysis, we identified six fractions with high peptide number and uniqueness that can account for 80% of the proteins identified in the entire experiment. These selected fractions were combined into a single sample which was then subjected to DIA (referred to as 2D-DIA) quantitative analysis. Furthermore, improved DIA quantification was achieved using a hybrid spectral library, obtained by combining peptides identified from DDA data with peptides identified directly from the DIA runs with the help of DIA-Umpire. The optimized 2D-DIA method allowed for improved identification and quantification of low abundant proteins compared to conventional unfractionated DIA analysis (1D-DIA). We then applied the 2D-DIA method to profile the proteomes of two breast cancer patient-derived xenograft (PDX) models, quantifying 6,217 and 6,167 unique proteins in basal- and luminal- tumors, respectively. Overall, this study demonstrates the potential of high-throughput quantitative proteomics using a novel 2D-DIA method.

Label-free Proteomics for Discovering Biomarker Candidates for Controlling Krypton Misuse in Castrated Horses (Geldings).

Recent advances in label-free quantitative proteomics may support its application in identifying and monitoring biomarkers for the purpose of doping control in equine sports. In this study, we developed a workflow of label-free quantitative proteomics to propose plasma protein biomarkers in horses after administration with krypton (Kr), a potential erythropoiesis-stimulating agent. Plasma proteomes were profiled by using nanoliquid chromatography-high-resolution mass spectrometry. An in-house mass spectral library consisting of 1121 proteins was compiled using samples collected from geldings (castrated horses) in the administration trial and geldings in training. A data-independent acquisition method was used to quantify an array of plasma proteins across plasma samples from the administration trial. Statistical analyses proposed a profile of 83 biomarker candidates that successfully differentiated Kr-administered samples from control samples, with the ability to detect Kr exposure for up to 13 days (the last sample collected in the administration trial). The model also correctly classified 32 in-training geldings as untreated controls. This is significantly longer than the 1 h detection time of plasma Kr using headspace gas chromatography-tandem mass spectrometry. Bioinformatic analyses enriched biomarker candidates relevant to complement activation and iron metabolism. The upregulation of transferrin receptor protein 1, one of the candidates related to iron metabolism, in plasma after Kr administration was validated by selected reaction monitoring of corresponding peptides. These results have demonstrated label-free quantitative proteomics as a promising approach to propose plasma protein biomarkers to enhance doping control. Data are available via ProteomeXchange with identifier PXD017262.